US6233572B1 - Computer implemented system and method for high level controlled searching through a problem space - Google Patents

Computer implemented system and method for high level controlled searching through a problem space Download PDF

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US6233572B1
US6233572B1 US09/322,430 US32243099A US6233572B1 US 6233572 B1 US6233572 B1 US 6233572B1 US 32243099 A US32243099 A US 32243099A US 6233572 B1 US6233572 B1 US 6233572B1
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subsearch
search
script
processes
executed
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James M. Crawford, Jr.
Brian M. Kennedy
Tiaohua Lin
Narayan Venkatasubramanyan
Arun Kunchithapatham
Karel Zeithammer
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Blue Yonder Group Inc
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q99/00—Subject matter not provided for in other groups of this subclass
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99932—Access augmentation or optimizing
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
    • Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y10S707/00—Data processing: database and file management or data structures
    • Y10S707/99931—Database or file accessing
    • Y10S707/99933—Query processing, i.e. searching
    • Y10S707/99935—Query augmenting and refining, e.g. inexact access

Definitions

  • This invention relates in general to the fields of supply chain management, and single- and multi-enterprise planning. More particularly, the present invention relates to a computer implemented system and method for high level controlled searching through a problem space.
  • Computer implemented planning systems are widely used for factory, enterprise and supply chain planning functions.
  • the systems model the manufacturing environment and provide plans for producing items to fulfill consumer demand within the constraints of the environment.
  • a classic artificial intelligence search can include elements such as: an initial state, a goal state, a termination criteria, and a set of moves between states of the search space.
  • an artificial intelligence search engine could have an initial state of a red block and blue block on a table and a yellow block on top of the blue block.
  • a goal state for such an engine could be the goal of building a planned sequence of moves which place the red block on top of the blue block.
  • the termination criteria could be to achieve the goal within 10 minutes or quit.
  • the set of moves could comprise: moving an uncovered block onto the table and moving an uncovered block from the table onto another uncovered block.
  • An artificial intelligence search process then, could compute a plan for the required moves to achieve the goal.
  • the number of “blocks” greatly increases, and the initial and goal states become more complex.
  • this type of search can be computationally challenging. Further complexity can be added to a system when the types and numbers of moves grow.
  • a computer implemented system and method for high level controlled searching through a problem space is disclosed that provides significant advantages over previously developed searching mechanisms.
  • the system can include a plurality of subsearch processes, wherein each subsearch process can comprise: a goal function, a termination criteria, a problem subset, a problem selection algorithm, a move subset, a lower subsearch set, and a script.
  • the problem subset can be an identified flaw, infeasibility, or suboptimal condition in a given system.
  • the problem selection algorithm is operable to select a targeted problem from the problem subset.
  • the move subset is a set of functions or operations operable to optimize the current subsearch.
  • the lower subsearch set is a set of one or more “downstream” subsearches.
  • the script is operable to specify or determine the appropriate moves or subsearches to execute.
  • FIG. 1 is a block diagram of a planning system that provides a mechanism for high level controlled searching through a problem space
  • FIG. 2 is a block diagram of one embodiment of a subsearch process for high level controlled searching through a problem space according to the present invention.
  • FIG. 1 is a block diagram of a planning system, indicated generally at 2 , that provides a mechanism for high level controlled searching through a problem space according to the present invention.
  • Planning system 2 can be implemented on a computer system having typical computer components such as a processor, memory, storage devices, etc.
  • planning system 2 executes software that implements a planning engine 3 in processor memory.
  • Planning engine 3 maintains and accesses a plan/model 4 representing, for example a manufacturing environment or supply chain which planning engine 3 is used to plan.
  • Planning engine 3 has access to data 5 stored in a fixed storage device. Data 5 can be used to initiate planning engine 3 and plan/model 4 .
  • Planning engine 3 and plan/model 4 are typically maintained in processor memory for speed and efficiency.
  • Planning engine 3 can provide information to a user via display 6 and can receive input data from input devices 7 .
  • planning engine 3 can execute the method of the current invention.
  • Plan/model 4 and data 5 can comprise the problem space upon which planning engine 3 operates.
  • Planning engine 3 can execute the subsearch process as depicted in FIG. 2 .
  • FIG. 2 is a block diagram of one embodiment of a subsearch process for high level controlled searching through a problem space according to the present invention.
  • Searching through the problem space can be achieved through the use of multiple subsearch processes 10 , each comprising: a goal function 12 , a termination criteria 14 , a problem subset 16 , a problem selection algorithm 18 , a move subset 20 , possible lower subsearches 22 , and a script 24 .
  • Subsearch process 10 is operable to modify the model/plan 4 .
  • Problem subset 16 can include a set of problems, where, for example, a problem is an identified flaw, constraint, infeasibility, or suboptimal condition in the current search state.
  • Problem selection algorithm 18 can include a method of selecting the next problem from the problem subset 16 to attack.
  • Move subset 20 can include operations or moves that are operable to transform the current search state into a better one.
  • Script 24 is operable to specify when to execute lower level subsearches 22 or a move from move subset 20 .
  • Higher level subsearch 30 of FIG. 2 illustrates that a plurality of subsearch processes 10 can be
  • an overall search could be modeled as a subsearch process 10 having neither a move subset 20 (or moves of its own) nor a higher level subsearch 30 .
  • Such an overall search could delegate the moves to lower level subsearches 22 and order the lower level subsearches 22 in a beneficial manner.
  • the present invention contemplates a scenario where lower level subsearches 22 can be viewed as “high level moves.” Individual moves of move subset 20 and lower level subsearches 22 can then be ordered together in the same script 24 .
  • Subsearch processes can be useful, for example, in manufacturing planning and scheduling applications, where user-intervention is critical.
  • One such example can be the planning of overtime shifts.
  • a human user (rather than the scheduling system) will often be in charge of planning overtime shifts.
  • a subsearch mechanism it is possible for a subsearch mechanism to take the user to a plan state in which orders are all delivered “on time” but under infeasible machine capacity conditions—thus necessitating further subsearching.
  • the subsearch process could include the components of TABLE 1.
  • TABLE 1 a goal function that specifies on time deliveries; a termination criteria of “no more late delivery problems”; a problem subset consisting of all problems whose resolution will not cause late delivery, this problem subset can exclude problems such as “machine capacity exceeded” or “material started before current time”; a problem selection algorithm which rates problems by latency and randomly selects a problem based upon the rating; a move subset of search space moves which are operable to avoid or eliminate late delivery problems; and no lower level subsearches.
  • a move such as “move task back in time” could help resolve late delivery problems, but a move such as “move task forward in time” could sometimes cause delivery problems.
  • a user could run this subsearch process, check machine capacities, and perhaps run some other subsearches which might resolve machine capacities. The user could then rerun this subsearch, schedule any necessary overtime shifts, and then run other subsearches to achieve a good plan under that overtime schedule. It is a technical advantage that the subsearch mechanism can provide users with several reasoning tools that are unavailable with other search mechanisms. It is another technical advantage of the present invention that searches with automated and manual features can be combined.
  • a further aspect of the present invention can provide for an entirely automated search mechanism.
  • a script could comprise the flow of TABLE 2.
  • Such an embodiment can implement a classic divide-and-conquer search strategy for dividing a slow-to-solve search into a series of fast-to-solve subsearches.
  • Such scripts can be implemented with a number of characteristics.
  • One characteristic is that a script can comprise a logical flow as shown in TABLE 3.
  • scripts can direct a subsearch process to run a series of subsearches and then terminate.
  • each subsearch can loop and attack (or apply moves from an associated move subset to) problems from an associated problem subset until the subsearch's termination criteria is met.
  • a script can operate to direct a subsearch to run a series of subsearches repeatedly.
  • the subsearch process could loop back and rerun the subsearches repeatedly until each subsearch has met its associated goal function, until a termination criteria is met, or upon manual termination.
  • Another characteristic is a script can operate to direct a subsearch process to run a series of subsearches repeatedly.
  • the subsearch process can loop and look for a subsearch with an associated goal function that has not been met and that has resolvable problems. If no such subsearch is found, the subsearch process can terminate. Otherwise, the subsearch process can run a single subsearch to attack one problem. Such an embodiment could terminate upon timeout or manual intervention.
  • a script can also operate to direct a subsearch process to loop until timeout or manual termination.
  • the subsearch process can select subsearches randomly weighted by a measure of how much work it will take to resolve problems associated with each subsearches. Each selected subsearch can be allowed to attack one of its associated problems.
  • a further aspect of a script is that it can offer one or more “hook” points for running lower level subsearches.
  • the script could include the flow of TABLE 4.
  • the annealing loop in the embodiment could be replaced with a user-supplied termination criteria.
  • a number of high level computer languages can be appropriate for expressing scripts. However, it can be desirable to integrate the language with the search engine. In such an embodiment, greater search control can be achieved as the amount of accessible state information is expanded.
  • a subsearch's subset of moves can contribute in several ways. For example, the subset can speed the search by focusing away from undesirable states (the problems the subsearch is working to eliminate). Additionally, a subsearch can help a user understand what has happened between subsearches. For example, in a subsearch which eliminates machine capacity problems, the user could see what happens if work is delayed (but never expedited). Alternatively, by changing the allowed moves, a user could see what happens if work is expedited (but never delayed). Bundling a subset of problems to work on and a subset of moves to do in that work gives the user a high level of control and insight into the overall search.
  • a top level subsearch could be organized as a sequence of three lower level subsearches, where the first subsearch deals with “big” problems, the second subsearch deals with “medium” problems, and the third subsearch deals with “small problems.”
  • “Problems” could mean any problem, a specific type of problem, problems at a specific point in the domain (such as a highly utilized factory machine). This organization can enable faster searching and be useful in situations that require manual intervention. For example, a user can solve the big problems, adjust the overtime schedule, and then re-execute the process to go back and solve the big problems the schedule adjustments created.
  • a further embodiment of the present invention can find an acceptable plan among various alternate plans.
  • Alternate plans can arise in various cases such as when a given item can be assembled using any of several operations (each of which may process different raw parts).
  • the script of such an embodiment could include the flow of TABLE 5.
  • the propagation_subsearch can model a plan for a system to build that quantity of item and solve upstream problems that might occur based on that plan (such as the need to assemble items that go into this particular assembly operation).
  • the evaluation_subsearch can evaluate the resultant plan, after running the propagation_subsearch, to ensure the resultant plan indeed builds the desired quantity. If so, the loop could be exited. Otherwise, the cleanup_subsearch could reset the plan so that the next alternate can be explored. For example, if propagation_subsearch built items upstream but fell short of the desired quantity, cleanup_subsearch can drive these quantity shortages downstream so that nothing is built downstream. Thus, the ‘problem’ can be restored, to be solved by the next alternate plan.
  • a user can achieve sophisticated search through combinations of alternate plans.
  • Another embodiment of the present invention can provide a general method of finding the best plan among various alternate plans.
  • Such an embodiment can comprise a similar subsearch process as the previously discussed embodiment.
  • the script can direct the subsearch process to explore all alternate plans and keep the best alternate.
  • the script of such an embodiment script comprises the flow as shown in TABLE 6.
  • an “undo point” can be set which allows the plan to be restored.
  • This embodiment can run similar subsearches as executed in the immediately prior described embodiment and store a particular alternate if the alternate is the best alternate of those explored so far.
  • the evaluation_subsearch target can narrow a search to a reasonable number of alternates or it could just return ‘false’ to have all alternates searched. After the search through alternates, the plan can be set to the best alternate encountered.

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US6912515B2 (en) * 2001-06-04 2005-06-28 Xerox Corporation Method and system for algorithm synthesis in problem solving
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US20080306922A1 (en) * 2004-08-09 2008-12-11 Research In Motion Limited System and method for enabling bulk retrieval of certificates
US20090199007A1 (en) * 2004-09-01 2009-08-06 Research In Motion Limited Providing certificate matching in a system and method for searching and retrieving certificates
US20100082976A1 (en) * 2004-09-01 2010-04-01 Research In Motion Limited System and method for retrieving related certificates
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Cited By (22)

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US6584532B1 (en) * 2000-05-17 2003-06-24 Arm Limited Branch searching to prioritize received interrupt signals
US20050203891A1 (en) * 2000-06-02 2005-09-15 Ns Holding Company Automated domain name registration
US8356081B2 (en) * 2000-06-02 2013-01-15 Verisign, Inc Automated domain name registration
US20020188488A1 (en) * 2001-04-30 2002-12-12 Hinkle Burl Shannon Methods and systems for simulating business operations
US6912515B2 (en) * 2001-06-04 2005-06-28 Xerox Corporation Method and system for algorithm synthesis in problem solving
US8301878B2 (en) * 2004-08-09 2012-10-30 Research In Motion Limited System and method for enabling bulk retrieval of certificates
US20080306922A1 (en) * 2004-08-09 2008-12-11 Research In Motion Limited System and method for enabling bulk retrieval of certificates
US8904170B2 (en) * 2004-08-09 2014-12-02 Blackberry Limited System and method for enabling bulk retrieval of certificates
US20130013917A1 (en) * 2004-08-09 2013-01-10 Research In Motion Limited System and method for enabling bulk retrieval of certificates
US20090199007A1 (en) * 2004-09-01 2009-08-06 Research In Motion Limited Providing certificate matching in a system and method for searching and retrieving certificates
US8296829B2 (en) 2004-09-01 2012-10-23 Research In Motion Limited Providing certificate matching in a system and method for searching and retrieving certificates
US8099593B2 (en) 2004-09-01 2012-01-17 Research In Motion Limited System and method for retrieving related certificates
US8561158B2 (en) 2004-09-01 2013-10-15 Blackberry Limited Providing certificate matching in a system and method for searching and retrieving certificates
US8589677B2 (en) 2004-09-01 2013-11-19 Blackberry Limited System and method for retrieving related certificates
US20100082976A1 (en) * 2004-09-01 2010-04-01 Research In Motion Limited System and method for retrieving related certificates
US8209530B2 (en) 2004-09-02 2012-06-26 Research In Motion Limited System and method for searching and retrieving certificates
US20100100730A1 (en) * 2004-09-02 2010-04-22 Research In Motion Limited System and method for searching and retrieving certificates
US8566582B2 (en) 2004-09-02 2013-10-22 Blackberry Limited System and method for searching and retrieving certificates
US8312165B2 (en) 2006-06-23 2012-11-13 Research In Motion Limited System and method for handling electronic mail mismatches
US20110029627A1 (en) * 2006-06-23 2011-02-03 Research In Motion Limited System and method for handling electronic mail mismatches
US8473561B2 (en) 2006-06-23 2013-06-25 Research In Motion Limited System and method for handling electronic mail mismatches
US8943156B2 (en) 2006-06-23 2015-01-27 Blackberry Limited System and method for handling electronic mail mismatches

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WO1999062018A1 (fr) 1999-12-02
TW440780B (en) 2001-06-16
KR20010070953A (ko) 2001-07-28
JP2002517044A (ja) 2002-06-11
EP1080440A1 (fr) 2001-03-07
AU4320099A (en) 1999-12-13
CA2333446A1 (fr) 1999-12-02

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